Single image rain and snow removal via guided L0 smoothing filter

被引:75
|
作者
Ding, Xinghao [1 ]
Chen, Liqin [1 ]
Zheng, Xianhui [1 ]
Huang, Yue [1 ]
Zeng, Delu [1 ]
机构
[1] Xiamen Univ, Sch Informat Sci & Engn, Fujian Key Lab Sensing & Comp Smart City, Xiamen, Peoples R China
基金
中国国家自然科学基金;
关键词
Single image rain and snow removal; Guided filter; L0 gradient minimization; Guided L0 smoothing filter; STREAKS REMOVAL; SPARSE;
D O I
10.1007/s11042-015-2657-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Since no temporal information can be exploited, rain and snow removal from single image is a challenging problem. In this paper, an improved rain and snow removal method from single image is proposed by designing a guided L0 smoothing filter. The designed filter is inspired by the previous L0 gradient minimization. Then a coarse rain-free or snow-free image can be obtained with the proposed filter, and the final refined result is recovered by a further minimization operation depending on the observed image. Experimental results show that the proposed algorithm generates better or comparable outputs than the state-of-the-art algorithms in rain and snow removal task for single image.
引用
收藏
页码:2697 / 2712
页数:16
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